WIAS Preprint No. 61, (1993)
Automatic bandwidth choice and confidence intervals in nonparametric regression.
Authors
- Neumann, Michael H.
2010 Mathematics Subject Classification
- 62G15 62G07 62G20
Keywords
- Nonparametric regression, bandwidth choice, confidence intervals, Edgeworth expansions
DOI
Abstract
In the present paper we combine the issues of bandwidth choice and construction of confidence intervals in nonparametric regression. We modify the √n-consistent bandwidth selector of Härdle, Hall and Marron (1991) such that it is appropriate for heteroscedastic data and show how one can adapt the bandwidth g of the pilot estimator m̂g in a reasonable data-dependent way. Then we compare the coverage accuracy of classical confidence intervals based on kernel estimators with data-driven bandwidths. We propose a method to put undersmoothing with a data-driven bandwidth into practice and show that this procedure outperforms explicit bias correction.
Appeared in
- Ann. Statist., 23 (1996), pp. 1937--1959
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